The present invention relates to automated systems for mounting electronic components to various carriers. Specifically, a system and method are described which can determine component dimensional data and store the data for use in an automated attachment tooling process.
The process of manufacturing electronic circuits on a volume basis has been significantly automated. As part of the automation process, components are mechanically and/or optically measured, and under control of a computer, placed on a ceramic substrate or printed circuit board for permanent attachment. These systems employ a robotic positioning system for grasping and then locating a component with respect to a substrate or printed circuit board, and include a machine vision capability to identify various features on the component. When using these devices in accordance with the prior art, the user enters the various dimensional information about a component in a database of the vision machine. Based on the stored information, the component is selected and visualized during placement by a machine having vision capabilities. Actual component features are compared with the stored dimensional data to determine the appropriate placement position and orientation of the component.
One such system for placing components such as flip chips on a substrate is the Adept Vision AGS System. The system includes a mechanical positioning device, as well as a vision system which generates a plurality of images from a 640xc3x97480 pixel CCD sensor array. During positioning of a component for placement on a circuit board or ceramic substrate, the individual components are viewed and dimensional information is automatically derived from the images of the components to determine their correct orientation and placement on the substrate.
These prior art xe2x80x9cpick and placexe2x80x9d systems rely upon the operator entering information about each component being observed in a database. The effort in verifying the various dimensional characteristics of the components which are to be entered in the database is tedious and prone to error. Further, the component manufacturing tolerances from component to component result in certain inaccuracies being present in the data entered in the database. These errors can produce placement errors when the components have dimensional characteristics different from those stored in the database.
The foregoing problems are exacerbated by the trend in the electronics industry toward array technology where components having an increasingly high pinout are placed in even smaller packages. An increase in pinout necessarily increases the dimensional information which must be inserted in the pick and place equipment for accurate location of the components. These include packages which support a solder bump array for making internal connections, chip scale packages, and flip chip devices for mounting on a circuit board.
It is an object of this invention to reliably determine dimensional information of a component being placed on a circuit board.
It is a more specific object of this invention to provide for optical measurement of component dimensional information, and for storing the information in a database for use during a pick and place operation.
These and other objects of the invention are provided for by a method and system in accordance with the invention. An automated pick and place system provides a component dimensioning operation which visually inspects each component to be mounted, and builds a database containing the component dimensional information.
Among the dimensional information obtained is the location of the component centroid which are stored in the database for use during part placement, and registration features of the component. Registration features provide an indication of component orientation and are used along with the centroid location for component placement. The registration features may be selected based on any number of user priorities, including maximum placement accuracy, maximum throughput, or a blend of accuracy and throughput maximization.